MAS: A Pretentious Technology for Selection of Superior Dairy Animals

Genomic exploration of dairy potentials of bovine resulted in many significant makers in cattle. Few of them are equally significant in buffaloes as well but many of them have not been found useful in buffalo. In present research, effect of genomic regions was studied for milk fat content by using candidate gene approach (CYP11b1, SCD and OLR1 genes). Animals were selected during first month of second lactation and were categorized into two groups for low and high fat content (n=250 in each group). Then PCR amplification, by specific primer sets, and DNA sequencing was performed on pools of high (> 8% butter fat) and low (<8% butter fat) fat containing groups of river buffaloes. Sequence alignment provided variations in the both groups. Two SNPs were identified in CYP11b1, 2 in SCD and 1 was found in OLR1 gene. Restriction enzymes were selected for the genomic variants and PCR-RFLP was performed at larger population (n=457). Association by One Way ANOVA revealed P17H in OLR1 gene and K158I in SCD gene was related to high fat content. Finally 3-D model of pertains was constructed and P17H was found in signal peptide of the OLR1 protein and K158I was found in transmembrane helix of SCD towards outer membrane of mitochondria and was found to enhance fat metabolism. Outcomes of the study are presenting the novel and informative genomic regions, which can be implemented in future buffalo breeding for selection of superior dairy animals.